System and method for enhanced transmitter efficiency

ABSTRACT

A method for distortion compensation in a transmission link comprising obtaining information of an amplitude distribution of a signal prior to being transmitted by a transmitter, receiving the transmitted signal at a receiver and determining a received signal amplitude distribution, comparing the received signal amplitude distribution to the amplitude distribution of the signal prior to transmission and using results of the comparison to estimate the AM/AM non-linearity in the transmitter.

FIELD OF THE DISCLOSURE

The present disclosure relates to linearization in a wireless radiolink, and particularly to a system and method for nonlinearitycompensation in a transmitter.

BACKGROUND

The quality of a signal in a communication system is affected by theamount of distortions introduced by the system during transmission. In atransmitter, and in particular, a power amplifier (PA) is one of themain sources of nonlinear distortions in the wireless radio transmissionlink. A plot of the output power of a PA as a function of input power iscalled the amplifiers compression curve 102, shown generally in FIG. 1.As input power increases and the output power of the amplifier is drivencloser to its maximum level, this relationship becomes non-linear. Thisnon-linear region 104 is usually referred to as the compression regionwhere equal increments of input power result in smaller increments ofoutput power. The gain 106 of the amplifier drops off in this region.Unfortunately, in order to maintain high power efficiency, the PA mustusually be operated in the compression region, which introducesconsiderable distortions to the signal.

The power spectral density of a transmitter's output is sometimesreferred to as the spectral emission. Nonlinear amplification of asignal may cause the signal to spread in the frequency domain intoadjacent frequency bands resulting in so-called extraneous emissions.Most communications standards set a limit on the spectral emissions of atransmitter. The shape of the spectral emission of the transmitter i.e.the emitted power density as a function of frequency is determined bythe specific type of signal modulation, as well as a statisticaldistribution of a baseband digital bit sequence. Given this informationthe shape of the spectral emission can be determined for an idealsystem. However system non-idealities skew this shape. The PAnon-linearity is one of the major sources of this non-ideality, whichoften tends to widen the bandwidth of the transmitted signal and raisethe power density level in the frequency regions neighboring thetransmission channel (spectral regrowth). A spectral mask is defined bystandards (such as those by the 3rd Generation Partnership Project(3GPP)) which sets a limit on the spreading of the power densityspectrum as well as extraneous emissions such as harmonics of thecarrier frequency or any unwanted spurious signals generated by theamplifier.

A PA's nonlinearity is sometimes evaluated using a metric called theadjacent channel power ratio (ACPR). The ACPR is defined as the ratio oftotal power within a certain bandwidth separate from the transmissionchannel, usually coinciding with the channel adjacent to thetransmission channel to the total power within the transmissionbandwidth.

In order to obtain an acceptable Bit Error Rate (BER) at the receiverend, linearization techniques may be used to compensate for thesedistortions while maintaining high power efficiency. Among the variousmethods for compensation, commonly used linearization techniques includedigital predistortion (DPD) and post-compensation at the receiver side.Without linearization, power back-off at the transmitter is required toobtain an acceptable BER, assuming that the channel is well equalized atthe receiver side and that the receiver is fully linear.

Pre-distortion is basically a method by which one first stimulates anon-linear PA with baseband samples and then observes the result of thatstimulus at the PA output. Then, the amplitude-to-amplitude modulation(AM/AM) and amplitude-to-phase modulation (AM/PM) effects of the PA areestimated. These estimated distortions are then removed from the PA bypre-distorting the input stimulus with their inverse equivalents. Inother words DPD consists of applying an inverse function having a gainwith an inverse amplitude and phase behavior of the complex gainbehavior of the PA to the signal before sending it to the poweramplifier. The cascaded pre-distortion function and the PA have acombined gain that is linear particularly in the compression region. Inorder to compensate for the complex gain distortion of the PA close tosaturation, the amplitude and phase are expanded relative to theoriginal input signal which causes an increase in the signalpeak-to-average power ratio (PAPR). Since the maximum power of the inputsignal is limited by the PA saturation, an increase in the PAPR forces adecrease in the mean input power (typically 2-4 dB). This power back offresults in decreased drain efficiency of the PA transistor(s). On theother hand, DPD performance is considerably affected by impairments inup and down-conversion circuits (such as feedback path components forexample mixers, filters, quadrature modulator and demodulator). Theseimpairments affect estimation of the inverse function of the PAbehavior.

Other techniques for DPD use training sequences to characterize the PAnonlinearity. In this approach, a training sequence is padded in eachframe and is sent to the receiver. At first, the effect of the channelis equalized. The resulting signal is then considered as the replica ofthe signal at the output of the PA. Based on the training sequence,which is known at the receiver side, the PA nonlinearity is extracted.The model is then sent to the transmitter for compensation.

SUMMARY

Prior predistortion techniques suffer from efficiency degradation, sincethe signal predistortion takes place at the transmitter side before thepower amplifier, which results in an increase in the peak-to-averagepower ratio of the signal. An embodiment of the present disclosureprovides a linearization method and system that compensates for thetransmitter nonlinearity at the receiver side in order to achieve highpower efficiency in the power amplifier. In other words thelinearization method and system of the present disclosure allows atransmitter PA to be operated closer to the compression region, toprovide better power efficiency.

According to an embodiment of the present disclosure the linearizationmethod and system provides for a cumulative distribution function (CDF)based algorithm to be used to estimate the PA's AM/AM nonlinearity at areceiver side of a wireless radio link.

According to a further embodiment the present disclosure, thelinearization system and method may be combined with transmitter-phasepredistortion along with the receiver-CDF-based amplitudepost-compensation for improving overall efficiency and BER performanceof the wireless radio link.

In accordance with an embodiment of the present matter there is provideda method for distortion compensation in a transmission comprising:

obtaining information of an amplitude distribution of a signal prior tobeing transmitted by a transmitter;

receiving the transmitted signal at a receiver and determining areceived signal amplitude distribution;

comparing the received signal amplitude distribution to the amplitudedistribution of the signal prior to transmission; and

using results of the comparison to estimate the AM/AM non-linearity inthe transmitter.

In accordance with a further aspect the method further includes applyingphase compensation predistortion to the signal before amplification byan amplifier in the transmitter.

In accordance with a still further aspect of the method there is furtherincluded using the estimate of the AM/AM non-linearity to derive acompensated signal.

In accordance with a still further aspect of the method there is furtherincluded applying a channel equalization prior to comparing theamplitude distributions.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure will be better understood with reference to thedrawings, in which:

FIG. 1 is plot of compression and gain curves for an amplifier;

FIG. 2 is a block diagram of radio link (transceiver) componentsaccording to an embodiment of the present matter;

FIG. 3 shows a spectrum of a measured received signal with and withoutPhase-DPD and a spectral mask according to an embodiment of the presentmatter;

FIG. 4 shows an AM/AM of an estimated nonlinearity and of a linearizedsystem according to an embodiment of the present matter;

FIG. 5 shows a block diagram of one estimation method, according to anembodiment of the present matter;

FIG. 6 shows a block diagram of a measurement setup according to anembodiment of the present matter;

FIG. 7 shows a spectrum emission mask of the WiMAX standard applied toan embodiment of the present matter;

FIG. 8 shows a spectrum emission mask of the LTE standard applied to anembodiment of the present matter;

FIG. 9 shows a receiver BER results versus SNR according to anembodiment of the present matter;

FIG. 10 shows a CDF of a transmitted and received signals with a Weibullfitted CDF to the transmitted signal according to an embodiment of thepresent matter;

FIG. 11 is a block diagram of an embodiment of a processing system; and

FIG. 12 is a block diagram of an embodiment of a communications device.

DETAILED DESCRIPTION OF THE DRAWINGS

The present disclosure describes a partition of distortion mitigationtechnique at both the transmitter and the receiver sides of the radiolink. The method compensates for the phase nonlinearity at thetransmitter side using phase digital predistortion (DPD) and mitigatesthe amplitude nonlinearity at the receiver side by analyzing thecumulative density function (CDF) of the received signal. The techniqueresults in more power efficient transmitter if less stringent linearityrequirements are tolerable. The channel effects have been alsoconsidered and are equalized before the amplitude nonlinearitycompensation in the receiver. The performance of the distributeddistortion compensation technique is compared, in terms of Error VectorMagnitude (EVM), Adjacent Channel Power Ratio (ACPR) and PowerEfficiency (PE). Measurement results show that the proposed partitioningdistortion mitigation approach provides an EVM of 1.2% and 1.7% forWiMAX and LTE signals respectively, compared to 1.3% and 1.7% for theconventional power back off (PBO) technique and 0.8% and 0.6% for thecomplex Digital Predistortion (DPD). Meanwhile the PE significantlyimproves from 5.6% and 14% for the conventional power back-off technique(PBO) to 10.8% and 19.2% using the proposed method. The BER values atthe receiver were then compared for the present method, the DPD andPhase-only DPD methods.

In systems using non-constant envelope modulations such as WCDMA(wideband code division multiple access), LTE (Long Term Evolution) andWiMAX (Worldwide Interoperability for Microwave Access), mobile handsetPAs are usually designed for quasi-linear operation. In other words,they are designed to be linear at specific back-off power from a peakpower.

To transmit the high PAPR signals with acceptable distortion, PAs areusually biased at class A or class AB. Furthermore, a large back-offfrom the peak power is applied for the PA to work linearly. This largeback-off causes a decrease in the power efficiency and hence increasesthe heat dissipation.

In DPD, the amplitude causes an increase in the PAPR and therefore powerefficiency degradation. However, phase nonlinearity compensation byitself does not affect the PAPR, and therefore does not degrade theefficiency of a mobile handset.

In OFDM (orthogonal frequency division multiplexing) for example, byknowing the amplitude distribution function (DF) of the original OFDMsignal (i.e. the signal prior to transmission), the amplitudenonlinearity of the PA can be estimated at the receiver side from acomparison between the distribution of the original signal before the PAamplification and the received signal.

Embodiments of the linearization method and system of the presentdisclosure do not require the use of a training sequence for thedistortion estimation purpose.

A method for distortion compensation according to the present disclosurecomprises transmitting a signal through a PA after equalizing thechannel effects at the receiver side; a baseband-equalized signal isused to estimate the amplitude nonlinear distortion using a cumulativedistribution function (CDF) of the received signal amplitude at thereceiver. The transmitter amplitude nonlinearity is compensated for inthe receiver side. Furthermore, the present method may includepre-distorting a phase nonlinearity at the transmitter. Still further,provided that the transmitted signal has reasonable amplitudenonlinearity, such that the transmitted signal may be expected tosatisfy an appropriate spectral mask.

A block diagram showing components of a radio link (transceiver)according to an embodiment of the present matter is shown, generally bynumeral 200, in FIG. 2. The radio link includes in order, a transmitside 202, a channel 204 and a receive side 206. The transmit side 202includes a transmitter having an optional phase-only compensationpredistortion block (Phase-DPD) 208 to which an RF modulated signal 210to be transmitted is fed. The input signal 210 has a known distributionfunction (DF). The output of the phase DPD 208 is passed through anup-converter 212 to a power amplifier 214. The output of the poweramplifier drives suitable transmission antenna (not shown) with anamplified signal (or pre-distorted amplified signal if the phase DPD isimplemented) which is transmitted along the transmission path or thecommunications channel 204. The receiver side 206 includes a receiveantenna (not shown) for receiving the transmitted signal over thecommunications channel 204, wherein the antenna is connected to a lownoise amplifier (LNA) 216, the output of the LNA 216 is passed through asuitable down-converter 218 and digitizer 220 before being fed to achannel equalization block 222 for equalizing the effects of the channel204 at the receiver side 206. The equalized signal is passed to adistribution comparison block 224 where a comparison is made between thedistribution of the original signal 226 before PA amplification and thereceived signal 228. This comparison produces an estimate of theamplitude-to-amplitude (AM/AM) nonlinear distortion 230, which may beused in a CDF based post compensation block 232 where the receivedbaseband equalized signal 228 is input and used along with the estimatedAM/AM non-linear distortion 230 to output a compensated signal 232. Thevarious blocks in FIG. 2 are described in more detail below.

The spectrum of the measured received signal (228 in FIG. 2) withPhase-DPD applied to the transmitted signal is shown by numeral 302 (theplot with the diamond symbol) in FIG. 3. The spectrum of the measuredreceived signal (228 in FIG. 2) without Phase-DPD applied to thetransmitted signal is shown by numeral 303 (the plot with the dotsymbol) in FIG. 3. An example spectral mask 304, for WiMAX at a 5 MHzbandwidth is also shown in FIG. 3. It may be seen that in both cases 302and 303, the received signal spectrum fits within the spectral mask 304.

Referring back to FIG. 2, if x and y denote the complex input and outputsignals, respectively, of the PA 214 and if r_(x) and r_(y) are theircorresponding amplitudes, a static power amplifier behavior can bemodeled in general as:

y=F(r _(x))exp(jG(r _(y)))x  (1)

where F(•) and G(•) are the AM/AM and the AM/PM nonlinear distortionfunctions of the PA, respectively. These functions vary with theamplitude of the input signal x.

If the input signal x distribution is known, then by estimating the CDFof the output signal y, the amplitude nonlinearity can be obtained. IfF₁ denotes the nonlinear function relating the amplitude of the outputsignal y to the amplitude of the input signal, then:

r _(y) =rF(r)=F ₁(r)  (2)

where, for simplicity, r is used instead of r_(x).

If F_(y)(•) and F_(x)(•) denote the CDFs of the output signal y andinput signal x, respectively, it is known that the followingrelationship holds between distributions of an output amplitude and aninput signal distribution in a system provided that the system transferfunction is monotonic:

F _(y)(r _(y))=F _(x)(r)  (3)

By Applying the inverse function of F₁ ⁻¹ to both sides of (2) one canwrite:

r=F ₁ ⁻¹(r _(y))  (3′)

By applying the inverse function of F_(x) ⁻¹ to both sides of (3) onecan write:

r=F _(x) ⁻¹[(F _(y)(r _(y))]  (3″)

Equating equations (3) and (3′) one can write that the inverse ofamplitude nonlinearity, F₁ ⁻¹(r_(y)) which is the post compensationfunction, can be estimated as follows:

F ₁ ⁻¹(r _(y))=F _(x) ⁻¹(F _(y)(r _(y)))=r  (4)

From Equation (4), it can be concluded that by knowing the CDFs F_(y)(•)and F_(x)(•) of the input and output signals respectively, one canobtain the nonlinearity function in the transmitter and compensate forit.

It is well established that, for example, most of the OFDM based signalsfollow a Rayleigh distribution, a generalized Rician distribution, orWeibull distribution. In the following, the theoretical analysis for theRayleigh, Rician and Weibull distributions are given as an example ofapplication of the CDF based compensation techniques to signals havingthese distributions. As will be appreciated other distribution may beused.

The Rayleigh distribution is given by:

$\begin{matrix}{{f\left( r \middle| b_{R} \right)} = {\frac{r}{b_{R}^{2}}{\exp \left( \frac{- r^{2}}{2b_{R}^{2}} \right)}}} & (5)\end{matrix}$

in which b_(R) is the scale parameter of the distribution. The Riciandistribution is given by:

$\begin{matrix}{{f\left( {\left. r \middle| a_{i} \right.,b_{i}} \right)} = {\frac{r}{b_{i}^{2}}{{\exp \left( \frac{- \left( {r^{2} + a_{i}^{2}} \right)}{2b_{i}^{2}} \right)} \cdot {I_{o}\left( \frac{r \cdot a_{i}}{b_{i}^{2}} \right)}}}} & (6)\end{matrix}$

where a₁ accordingly is an indication of the distance between thereference point and the center of the bivariate distribution and b₁ isthe scale parameter, and I_(o)(•) denotes a Bessel function of the firstkind.

The Weibull distribution is given by:

$\begin{matrix}{{{f\left( {\left. r \middle| b_{W} \right.,c_{W}} \right)} = {\frac{c_{W}}{b_{W}}\left( \frac{r}{b_{W}} \right)^{c_{W} - 1}{\exp \left( {- \left( \frac{r}{b_{W}} \right)^{c_{W}}} \right)}}}{{r \geq 0},{b_{W} > 0},{c_{W} > 0}}} & (7)\end{matrix}$

where c_(W) is the shape and b_(W) is the scale parameters of theWeibull distribution.

Below are described example embodiments of the present disclosure whichshow mitigation of the nonlinearity in a transmitter using the CDF ofthe signal received at the receiver. The nonlinearity is expressed asfunctions of the CDF are described for the cases of Rayleigh and Weibulldistributions. In these cases, the amplitude nonlinearity can beestimated using the following formulas:

$\begin{matrix}{{F_{1}^{- 1}\left( r_{y} \right)} = \sqrt{{- 2}b_{R}^{2}{\ln \left( {1 - {F_{y}\left( r_{y} \right)}} \right)}}} & (8) \\{{F_{1}^{- 1}\left( r_{y} \right)} = {b_{W}\left( {- {\ln \left( {1 - {F_{y}\left( r_{y} \right)}} \right)}^{\frac{1}{c_{W}}}} \right)}} & (9)\end{matrix}$

Example plots in a graph of normalized input power versus AM/AM forresults of the estimation of the nonlinearity using CDF and thelinearized system AM/AM behaviors according to embodiments of thepresent disclosure are shown in FIG. 4. A received signal plot 402(shown with circular symbols), an estimated nonlinearity 404 (shown withdiamond symbols) and the compensated signal 406 (shown with squaresymbols) are shown in FIG. 4. As may be seen from the figure the CDFbased nonlinearity compensation method of the subject disclosurereasonably estimates the nonlinearity and compensates for it.

A flow chart 500 for estimating and mitigating transmitter nonlinearityaccording to an embodiment of the present disclosure is shown FIG. 5. Afirst step in estimating the AM/AM is to fit a parametric CDF to thetransmitted signal amplitude, as shown in block 502. A maximumlikelihood estimation (MLE) of the parameters can be obtained throughsimple averaging of proper statistics. For instance in the case ofWeibull distribution, the parameters can be estimated using thefollowing equations. If it is assumed that r₁, . . . , r_(N) are thesamples of the transmitted frame and R_(i)=ln(r_(i)), then the MLEestimated values, ĉ_(W) and {circumflex over (b)}_(W), for the Weibullparameters can be obtained as below:

$\begin{matrix}{{\hat{c}}_{W} = \left( {\frac{\sum\limits_{i = 1}^{N}{r_{i}^{{\hat{c}}_{W}}R_{i}}}{\sum\limits_{i = 1}^{N}r_{i}^{{\hat{c}}_{W}}} - \overset{\_}{R}} \right)^{- 1}} & (10) \\{{\hat{b}}_{W} = \left( {\frac{1}{N}{\sum\limits_{i = 1}^{N}r_{i}^{{\hat{c}}_{W}}}} \right)^{\frac{1}{c_{W}}}} & (11)\end{matrix}$

where R denotes the average value of R_(i).

At block 504 the parameters of the CDF are sent to the receiver. Thismay be done in many different ways know in the art. For example using adifferent channel. At block 506 the next step in estimating the AM/AM atthe receiver is to estimate the CDF of the received signal. Since, thePA nonlinearity is not known at the receiver side, parametric CDFestimation may be unreasonable. As a result, empirical methods may beemployed to obtain the CDF. Among empirical CDF estimation techniques,Kaplan-Meier is an example of a technique that has been found to besimple and accurate. In this approach the survival function of a randomvariable r with a CDF F(r) is estimated as:

P(r)=1−F(r)  (12)

To estimate the survival function, the scale is divided to N intervalsnamely: [0 r₁], . . . , [r_(N-1) r_(N)]. Then P(r) can be estimated asbelow:

$\begin{matrix}{{P(r)} = {\prod\limits_{r_{i} < r}\; \left( \frac{n_{i} - d_{i}}{n_{i}} \right)}} & (13)\end{matrix}$

where n_(i) is the number of samples greater than r_(i-1) and d_(i)represents the number of observations that are greater than r_(i-1) butsmaller than r_(i).

As may be seen with the present method, phase distortion can becompensated at the transmitter without deteriorating the efficiency,since, the PAPR will not change and there is no need for a powerback-off. Another advantage of the subject method is that, in general,the phase nonlinearity is less sensitive to the PAPR of the signal. Thephase DPD can likely be implemented independently from the signaldistribution and PAPR without being adaptive.

An example of implementing phase nonlinearity compensation at thetransmitter side uses a simple LUT, which can be estimated using a highPAPR signal and then reused for other standards and with any PAPR.

Measurement results for different linearization techniques, i.e. DPD,PBO and distributed distortion compensation, are described whichcompares the performance of the present disclosure to conventionaltechniques. The comparison is carried out in terms of Power Efficiency(PE), Error Vector Magnitude (EVM), Normalized Mean Square Error (NMSE)and Adjacent Channel Power Ratio (ACPR).

A measurement setup may consist of a vector signal generator, a driveramplifier, a PA, an attenuator and a vector signal analyzer (VSA), isshown in FIG. 6.

Six different excitation signals are uploaded to the signal generatorusing a general-purpose interface bus (GPIB). The specifications ofthese excitation signals for system identification and evaluation aresummarized in Table I.

Two different device-under-tests (DUTs), each composed of a class-AB PAsuitable for mobile stations, where used in the measurement.

TABLE I Parameters of the modulated signals Signal PARR BandwidthSampling Number Standard (dB) (MHz) Frequency (MHz) 1 WiMAX 10.2 5 92.162 WiMAX 12.7 5 92.16 3 LTE 10.4 5 61.44 4 LTE 12.4 5 61.44 5 WCDMA 93.84 92.16 6 WCDMA 10.9 3.84 92.16

In a first scenario, the channels were assumed to be ideal. Theperformance of the proposed distributed distortion compensationtechnique in terms of power efficiency and linearity is compared to thePBO and MP-DPD techniques in example of practical scenarios for uplinktransmissions using two different wireless communication standards:WiMAX and LTE. These standards are provided as non-restrictive examplesof application.

The measurement results for all the three above mentioned approaches arelisted in Tables II and III. As is evident from the tables, MP-DPD hasthe highest PAPR before PA. As discussed before, an increase in the PAPRbefore PA causes an increase in the amount of back-off needed fordriving the PA which in turn limits the improvement in efficiency.

TABLE II Measurement results for WiMAX PAPR Method PAPR before ACPR1ACPR2 EVM Eff. WiMAX (dB) PA (dB) (dBc)L, H (dBc)L, H (%) (%) No 11.411.4 −37.7 −57.1 3.4 10.8 Compensation −38.2 −57.6 DPD 11.4 15.4 −46.5−56.9 0.8 4.4 −46.9 −57.3 BO@3 dB 11.4 11.4 −45.1 −60 1.3 5.6 −45.6−60.2 PC 11.4 11.4 −38.7 −57.5 1.2 10.8 −39.1 −58.2

TABLE III Measurement results for LTE PAPR Method PAPR before ACPR1ACPR2 EVM Eff. LTE (dB) PA (dB) (dBc)L, H (dBc)L, H (%) (%) No 7.8 7.8−30 −44 5.9 23.4 Compensation −30.5 −44.5 DPD 7.8 11.4 −42.5 −51.5 0.611 −43.3 −51.7 BO@2.5 dB 7.8 7.8 −37.1 −50.7 1.7 14 −37.8 −51.1 PC@1 dBBO 7.8 7.8 −33.8 −48.9 1.7 19.2 −34.4 −49.5

Concerning the spectral emission and ACPR requirements, all the methodscould satisfy the ACPR requirements. FIGS. 7 and 8 show the spectrumemission masks of the WiMAX and LTE standards respectively along withthe spectrums of input signal, phase-only DPD, PBO, fully driven PAoutput, MP-DPD.

In the second scenario, the effect of an additive white Gaussian noisechannel is considered. The performance of the present invention iscompared to DPD and back-off methods in terms of BER variation as afunction of Signal to Noise Ratio (SNR).

FIG. 9 shows the receiver BER results versus SNR. As is shown in FIG. 9,the proposed technique could reasonably reduce the BER as the SNRincreases to reach similar performance compared to the DPD technique.FIG. 10 shows a CDF of a transmitted and received signals with a Weibullfitted CDF to the transmitted signal.

In this disclosure, a method and an architecture for PA distortioncompensation is described which may be applied to both uplink anddownlink applications. According to embodiments of the present matterdistortion compensation is partitioned between the transmitter and thereceiver, where the transmitter may include a LUT-based phase-onlypredistortion and the receiver comprises a CDF-based amplitudenonlinearity estimation and post-compensation. The amplitudenonlinearity is compensated at the receiver after channel equalizationand does not require any training sequence. It only requires no morethan two parameters for the signal distribution for most of the wirelesssignals to be known by the receiver. The distributed distortioncompensation technique replaces the conventional back-off approach orthe full DPD approach. The example implementation results describedherein show that the distributed distortion compensation according tothe present matter provides almost the same linearity and reasonable BERperformance as conventional techniques, but with considerableimprovement in power efficiency.

The methods, devices and systems described herein may be used in or withany computing system or device including but not limited to userequipments, mobile devices, node Bs, base stations, network elements,transmission points, machines, chips, etc. For example FIG. 11 is ablock diagram of a processing system 1100 that may be used with themethods and devices according to the present disclosure. Specificdevices may utilize all of the components shown, or only a subset of thecomponents, and levels of integration may vary from device to device.Furthermore, a device may contain multiple instances of a component,such as multiple processing units, processors, memories, transmitters,receivers, etc. The processing system 1100 may comprise a processingunit equipped with one or more input/output devices, such as a speaker,microphone, mouse, touchscreen, keypad, keyboard, printer, display, andthe like. The processing system may include one or more of a processor1110, memory 1120, a mass storage device 1130, a video adapter 1140, andan I/O interface 1150 connected to a bus 1160. In at least oneembodiment, processor 1110 may be multi-core or a many-core processor,or any other processor having multiple execution units, for example forexecuting one or more methods according to the present disclosure.

The bus 1160 may be one or more of any type of several bus architecturesincluding a memory bus or memory controller, a peripheral bus, videobus, or the like. The memory 1120 may comprise any type of system memorysuch as static random access memory (SRAM), dynamic random access memory(DRAM), synchronous DRAM (SDRAM), read-only memory (ROM), a combinationthereof, or the like. In an embodiment, the memory may include ROM foruse at boot-up, and DRAM for program and data storage for use whileexecuting programs.

The mass storage device 1130 may comprise any type of storage deviceconfigured to store data, programs, and other information and to makethe data, programs, and other information accessible via the bus. Themass storage device 1630 may comprise, for example, one or more of asolid state drive, hard disk drive, a magnetic disk drive, an opticaldisk drive, or the like.

The video adapter 1140 and the I/O interface 1150 provide interfaces tocouple external input and output devices to the processing system. Asillustrated, examples of input and output devices include the display1142 coupled to the video adapter and the mouse/keyboard/printer 1152coupled to the I/O interface. Other devices may be coupled to theprocessing system, and additional or fewer interface cards may beutilized. For example, a serial interface such as Universal Serial Bus(USB) (not shown) may be used to provide an interface for a printer.

The processing system 1100 also includes one or more network interfaces1170, which may comprise wired links, such as an Ethernet cable or thelike, and/or wireless links to access nodes or different networks. Thenetwork interface 1170 may allow the processing system to communicatewith remote units or systems via the networks. For example, the networkinterface 1170 may provide wireless communication via one or moretransmitters/transmit antennas and one or more receivers/receiveantennas. In an embodiment, the processing system 1100 may be coupled toa local-area network or a wide-area network, shown as network 1172, fordata processing and communications with remote devices, such as otherprocessing systems, the Internet, remote storage facilities, or thelike.

FIG. 12 illustrates a block diagram of an embodiment of a communicationsdevice or system 1200, which may be equivalent to one or more devices(e.g., user equipments, node Bs, base stations, network elements,transmission points, machines, chips, etc.) discussed above. Thecommunications device 1200 may include one or more processors 1204, suchas for example a multi-core or a many-core processor. Communicationsdevice 1200 may further include a memory 1206, a cellular interface1210, a supplemental wireless interface 1212, and a supplementalinterface 1214, which may (or may not) be arranged as shown in FIG. 12.The processor 1204 may be any component capable of performingcomputations and/or other processing related tasks, and the memory 1206may be any component capable of storing programming and/or instructionsfor the processor 1204. The cellular interface 1210 may be any componentor collection of components that allows the communications device 1200to communicate using a cellular signal, and may be used to receiveand/or transmit information over a cellular connection of a cellularnetwork. The supplemental wireless interface 1212 may be any componentor collection of components that allows the communications device 1200to communicate via a non-cellular wireless protocol, such as a Wi-Fi orBluetooth protocol, or a control protocol. The device 1200 may use thecellular interface 1210 and/or the supplemental wireless interface 1212to communicate with any wirelessly enabled component, e.g., a basestation, relay, mobile device, etc. The supplemental interface 1214 maybe any component or collection of components that allows thecommunications device 1200 to communicate via a supplemental protocol,including wire-line protocols. In embodiments, the supplementalinterface 1214 may allow the device 1200 to communicate with anothercomponent, such as a backhaul network component.

Through the descriptions of the preceding embodiments, the teachings ofthe present disclosure may be implemented by using hardware only or byusing a combination of software and hardware. Software or other computerexecutable instructions for implementing one or more embodiments, or oneor more portions thereof, may be stored on any suitable computerreadable storage medium. The computer readable storage medium may be atangible or in transitory/non-transitory medium such as optical (e.g.,CD, DVD, Blu-Ray, etc.), magnetic, hard disk, volatile or non-volatile,solid state, or any other type of storage medium known in the art.

We claim:
 1. A method for distortion compensation in a transmission linkcomprising: obtaining information of a signal transmitted by atransmitter; receiving the transmitted signal at a receiver; comparingthe received signal to the signal transmitted prior to transmission; andusing results of the comparison to post-compensate at the receiver forlinear and non-linear distortions in the transmission link.
 2. A networkelement comprising: a receiver for receiving a signal after transmissionfrom a transmitter; a processor configured to: obtain information of asignal transmitted by a transmitter, receive the transmitted signal atthe receiver, compare the received signal to the signal transmittedprior to transmission; and use results of the comparison topost-compensate at the receiver for linear and non-linear distortions inthe transmission link.
 3. The network element of claim 2, wherein thenetwork element is a mobile device.
 4. The network element of claim 2,wherein the network element is a base station.
 5. The method of claim 1,wherein the receiver is a mobile device.
 6. The method of claim 1,wherein the receiver is a base station.
 7. The method of claim 1,wherein the transmission link is a downlink between an electronic deviceand a base station.
 8. The method of claim 1, wherein the transmissionlink is an uplink between an electronic device and a base station. 9.The method of claim 1, further including: obtaining phase information ofthe signal at an input and output of the transmitter before saidtransmission; comparing the phase of the input and output of thetransmitted signal; using the comparison of the phases to estimate theAM/PM non-linearity in the transmitter, and linearizing the transmittedsignal using a phase-only predistortion at the transmitter.
 10. Thenetwork element of claim 2, furthermore comprises a processor in thetransmitter configured to: obtain information of the signal at an inputand output of the transmitter before being transmitted; compare thesignals at the input and output of the transmitter; and use thecomparison to pre-compensate at least partially for an AM/PMnon-linearity in the transmitter.
 11. The method of claim 10, theprocessor further configured to use the signal comparison topre-compensate partially for the AM/AM non-linearity in the transmitter.12. The method of claim 10, wherein the comparison is used to estimatethe AM/PM non-linearity in the transmitter.
 13. The method of claim 10,wherein the comparison is used to estimate the AM/AM non-linearity inthe transmitter.
 14. The method of claim 1, further includingimplementing a phase-only predistortion at the transmitter prior totransmission of said signal.
 15. The network element of claim 2, whereina phase-only predistortion of the signal prior to transmission isimplemented.